Papers
2
Total Citations
8
H-Index
2
About
Shihao Ge is a robotics researcher focused on advancing autonomous manipulation in complex, unstructured environments. His work bridges computer vision and adaptive control, with key contributions in medical automation and agricultural robotics. In his highly cited 2023 study, Ge developed a pixel-level collision-free grasp prediction network for sorting medical test tubes on cluttered trays—a critical step toward automating laboratory workflows. This work addresses the fundamental challenge of vision-based grasp detection in crowded, unpredictable settings, achieving robust performance where traditional methods fail. More recently, Ge has explored humanoid underactuated manipulators for fruit grasping, introducing an adaptive algorithm that generalizes across fruit types without task-specific programming. His approach enhances both grasping stability and adaptability, overcoming the limitations of conventional predefined control systems. With over 8 total citations and growing recognition, Ge’s research is shaping the next generation of dexterous robotic hands for healthcare and agriculture. His work exemplifies how integrating perception with flexible mechanical design can unlock new capabilities for robots operating in the real world.
Research Focus
Key Achievements
Top Papers
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